Staff Software Engineer, Leverage

Description

Fleetio is seeking a Staff Software Engineer to be the founding engineer on our new Leverage team. The Leverage team's mandate is to make every person at Fleetio more productive by building the knowledge infrastructure that connects our internal data to the AI tools employees already use every day. At other companies, this work falls under "productivity engineering" or "internal tools." We call it Leverage because the scope is broader: serve the entire company, not just engineering.

This is not a blank slate. Fleetio engineers are already using AI tools daily, and an organic ecosystem of shared skills and integrations has emerged across the engineering org. You will build on that momentum, not start from zero. Your job is to add the enterprise capabilities this ecosystem needs to scale: identity and auth, structured access to internal data, governance, and quality standards. You will design and build the context layer that connects Fleetio's distributed knowledge to the AI tools our team already uses. You will work directly with the Leverage team lead, and together you will define the technical direction for everything this team builds.

This is a remote opportunity open to candidates in the United States, Canada, or Mexico.

More About Our Team and Company

• Watch our culture videos: https://fleet.io/culture
• Engineering culture, interview process, and videos: https://www.fleetio.com/careers/engineering
• Fleetio Go overview video: https://www.fleetio.com/go
• More about the Fleetio platform: https://www.fleetio.com/features
• API docs: developer.fleetio.com
• Test drive Fleetio to get an even better feel for what we're building: https://www.fleetio.com/register

This is a remote opportunity and is open to candidates in the United States, Canada, or Mexico.

Who you are

You are a staff-level, systems-minded engineer who gets energy from building tools that make other people more effective. You have deep experience integrating across SaaS APIs and are comfortable navigating the messiness of inconsistent auth models, pagination, rate limits, and data formats. You would rather build one system that enables 50 integrations than build 50 one-off integrations.

You are comfortable operating in ambiguous, cross-functional spaces. You talk to users before you write code. You care about adoption, not just shipping, and you understand that internal tools fail when they have bad UX or no adoption strategy. You bring strong opinions about developer productivity, loosely held, and you communicate clearly with both engineers and non-technical stakeholders.

You are product-minded and team-oriented, willing to hear others' perspectives and educate on best practices. Excellent communication skills, particularly written, are essential.

Your impact

• Design and build the knowledge infrastructure that gives AI tools at Fleetio structured access to company context. The form this takes (an API layer, a CLI, an SDK, agent configuration, protocol servers, or something new) is a decision you will help make.
• Build integrations that connect Fleetio's internal knowledge sources (project management, documentation, code, data warehouses, communication tools) into a consistent, secure context layer with identity passthrough.
• Design the system so other teams can extend it. Whether that means spoke templates, plugin architectures, or shared configuration patterns, the goal is to scale beyond what a small team can maintain directly.
• Partner with teams across Fleetio to identify where missing context creates the most friction, and build the integrations that close those gaps. This is not engineering-only: Product Managers need AI tools that understand product strategy and customer data; designers need access to design systems and user research; Customer Success needs account history and help center content.
• Take ownership of CI/CD intelligence, making pipelines fast, reliable, and trustworthy as AI-accelerated development increases code velocity.
• Define and own the measurement framework for AI adoption and internal tool impact across the company. Track what works, surface what doesn't.
• Champion AI-first documentation practices: structure internal docs so AI tools can consume them effectively (coding examples, machine-parseable formats, clear interface descriptions).
• Collaborate closely with the Platform/SRE team (they own infrastructure; we build the tooling and knowledge layer on top) and with Product Managers, Designers, and Engineers across the organization.
• Produce well-tested, maintainable, and performant code. Thoroughly review your peers' code to ensure quality, maintain consistency, and share knowledge.
• Contribute enterprise-grade capabilities to Fleetio's existing internal AI tooling ecosystem: identity and auth for protected systems, governed data access, cross-system queries, and quality patterns that help the ecosystem scale.
• Establish the technical standards for the Leverage team. As the founding engineer, your decisions on architecture, tooling, and code quality will set the bar for everyone who follows.

Your experience

• 5+ years of professional experience building production software
• Strong integration engineering skills: comfort working across dozens of APIs, authentication schemes (OAuth, API keys, SAML, service accounts), data formats, and rate limits
• Experience with protocol-based architectures (MCP, LSP, or similar), SDKs, CLI tooling, or developer platform design. You understand how to expose structured data to client tools in a way that scales.
• Full-stack capabilities: you will build backend services, CLI tools, and internal UIs
• Experience with identity and access management (Okta, SSO, or similar) and understanding of how to pass user identity through to downstream systems
• Experience building and consuming APIs and working with external integrations
• Solid experience solving challenging architecture problems with good design
• Experience with unit testing frameworks and CI/CD pipelines
• Excellent communication skills, particularly written
• Be sure to mention "coffee" in your application so we know you actually read this

Considered a plus

• Comfort working in a Rails shop
• Experience building internal tools, developer platforms, or developer experience tooling
• Track record integrating across multiple SaaS APIs, with firsthand knowledge of inconsistent auth, pagination, and rate limiting
• Experience on a small team (2-5 people) where you owned significant portions of the product
• Hands-on experience with AI coding tools (Copilot, Codex) and an understanding of what makes them effective vs. ineffective
• Experience at a company that invests seriously in internal tooling (Stripe, Shopify, Block, etc.)
• Familiarity with workflow automation platforms (n8n, Zapier, Workato, or similar)
• Experience contributing to or maintaining shared developer tooling ecosystems (internal package registries, shared libraries, plugin systems)
• Familiarity with AI agent skill/tool architectures (Codex skills, MCP tools, function calling patterns)
• Experience with Snowflake, PostgreSQL, or similar data platforms
• You know a thing or two about the fleet management industry